---
title: "Mobility score!"
output:
flexdashboard::flex_dashboard:
orientation: columns
vertical_layout: fill
theme: spacelab
source_code: embed
fontsize: 16pt
---
```{r setup}
library(knitr)
library(kableExtra)
library(flexdashboard)
library(WDI)
library(tidyverse)
library(plotly)
library(crosstalk)
library(ggthemes)
library(DT)
library(scales)
library(reactable)
library(lubridate)
library(hrbrthemes)
library(htmltools)
library(sparkline)
library(dplyr)
myfont="Times New Roman"
knitr::opts_chunk$set(echo = FALSE)
source("C:/Users/momenifi/Dropbox/OASE/dashboard/JOI/data_mobility.R",local = knitr::knit_global())
m_score_distrubtion<-variables%>%group_by(GENDER, MAIN_FIELD) %>% count(m_score)
m_score_distrubtion_filtered<-filter(m_score_distrubtion,m_score<10)
m_score_distrubtion_filtered$GENDER<-ifelse(m_score_distrubtion_filtered$GENDER==0,"female","male")
shared_m_score <- SharedData$new(m_score_distrubtion_filtered)
#####Distribution of mobile researchers based on mobility score
g<-ggplot(aes(x=m_score,y=n,fill = GENDER),data=shared_m_score)+
geom_bar(position="dodge", stat = "identity")+ theme(legend.position="top",
legend.title=element_blank())
gg<-ggplotly(g)
bscols(widths = c(2,2,12,12),
div(style = css(width="2%", height="2px", background_color="gray")),
list(
filter_select(id = "GENDER", label = "Gender",
sharedData = shared_m_score, group = ~ GENDER,multiple=T,allLevels = FALSE),
filter_select(id = "MAIN_FIELD", label = "scientific field",
sharedData = shared_m_score, group = ~ MAIN_FIELD,multiple=F,allLevels = FALSE)
),
gg)
```
```{css}
.bar-cell {
display: flex;
align-items: center;
}
.number {
font-size: 13.5px;
white-space: pre;
}
.bar-chart {
flex-grow: 1;
margin-left: 6px;
height: 22px;
}
.bar {
height: 100%;
}
```